KL divergence between a general distribution and a perturbed Gaussian reference remains stable with an optimal sqrt(ε) degradation rate under finite second-moment conditions.
On measures of entropy and information,
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Derives closed-form Rényi rate-distortion-perception functions for Gaussian sources showing a feasible variance interval under perception constraints and establishes a Rényi-generalized strong functional representation lemma with alpha-dependent phase transitions in coding complexity.
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Optimal Stability of KL Divergence under Gaussian Perturbations
KL divergence between a general distribution and a perturbed Gaussian reference remains stable with an optimal sqrt(ε) degradation rate under finite second-moment conditions.
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On the R\'enyi Rate-Distortion-Perception Function and Functional Representations
Derives closed-form Rényi rate-distortion-perception functions for Gaussian sources showing a feasible variance interval under perception constraints and establishes a Rényi-generalized strong functional representation lemma with alpha-dependent phase transitions in coding complexity.